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Dynamic Electrical Impedance Tomography Image Reconstruction of Neonate Lung Function based on Linear Kalman Filter techniques

机译:基于线性卡尔曼滤波技术的新生儿肺功能动态电阻层析成像图像重建

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Electrical impedance Tomography (EIT) has great potential as a low cost continuous monitoring system for neonate lung function. However EIT data obtained from clinical measurements are inherently noisy and require reconstruction algorithms that are robust enough to cope with these difficulties. In this paper, we examine the potential of a linear Kalman approach for EIT difference imaging. Simulated data is used for the reconstruction process; real time-data is being tested and the results will be introduced at a latter stage of this research. Our objective is to use this initial research to develop a nonlinear Kalman filter for frequency difference imaging of neonate lung function.
机译:电阻抗断层扫描(EIT)作为低成本的新生儿肺功能连续监测系统具有巨大的潜力。然而,从临床测量获得的EIT数据本质上是嘈杂的,并且需要足够强大的重建算法来应对这些困难。在本文中,我们研究了线性卡尔曼方法用于EIT差异成像的潜力。模拟数据用于重建过程;正在测试实时数据,并将在本研究的后期介绍结果。我们的目标是利用这项初步研究开发出非线性Kalman滤波器,用于新生儿肺功能的频差成像。

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